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Graph-based analysis of EEG for schizotypy classification applying flicker Ganzfeld stimulation
Ahmad Zandbagleh1, Sattar Mirzakuchaki2, Mohammad Reza Daliri1
1School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.
Schizophrenia (Heidelberg, Germany)
|September 21, 2023
Summary
Individuals with low positive schizotypy exhibit more efficient brain networks during Ganzfeld conditions. Graph theory analysis accurately classifies brain states, especially during anxiety, suggesting potential for psychosis research.
Area of Science:
- Neuroscience
- Psychophysiology
- Network Science
Background:
- Ganzfeld conditions alter brain function and can induce pseudo-hallucinatory experiences, particularly in individuals with high positive schizotypy.
- Understanding brain network differences based on schizotypy levels is crucial for exploring altered perceptual experiences.
Purpose of the Study:
- To investigate and classify brain networks under Ganzfeld conditions using graph-based parameters as a function of positive schizotypy.
- To explore the relationship between brain functional states, Ganzfeld stimulation, and individual differences in positive schizotypy.
Main Methods:
- Electroencephalography (EEG) assessment of 14 high schizotypy (HS) and 29 low schizotypy (LS) participants under Ganzfeld conditions with varied visual and auditory stimuli.
- Computation of weighted functional brain networks across six frequency sub-bands (delta, theta, alpha, beta, gamma).
- Analysis using graph theory parameters (clustering coefficient, strength, global efficiency) and classification via the RUSBoost algorithm.
Main Results:
- Low schizotypy (LS) groups demonstrated higher clustering coefficient and strength, particularly in temporal and frontotemporal regions, compared to high schizotypy (HS) groups.
- LS groups exhibited significantly higher global efficiency across all Ganzfeld conditions.
- The RUSBoost algorithm achieved 95.34% classification accuracy for brain states during anxiety-induction, with high specificity and sensitivity.
Conclusions:
- This study provides the first exploration of brain functional state changes under Ganzfeld conditions in relation to positive schizotypy.
- Graph-based parameters effectively classify brain states associated with schizotypy, especially during anxiety-inducing conditions.
- Findings suggest potential for further investigation in psychosis research.
